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Month: December 2015

The end of the year is a natural time for retrospection. When I started this blog, more than a year and a half ago, I aimed to cover a pretty broad domain, where the predominant filter, beyond this loose boundary, was sharing content that passed my personal bar of being share-worthy. But when I took a step back and looked at all the content I shared this year, four distinct themes emerged. Here are this year’s blog posts, categorized by these themes:

In this post, Adrian applies Michael Kramer’s O-Ring Theory of Economic Development to the realm of DevOps. but in my mind, the most interesting applicability of this theory is at a context somewhere between the massive scale of economic development and the targeted scale of DevOps: the context of organizational operations and talent management in particular.

In a nutshell the O-ring theory, inspired by the 1986 Challenger disaster where a single failure of an O-ring lead to catastrophic results, shows how small changes in quality lead to massive changes in output/productivity.

The theory applies in scenarios that meet the following three conditions:

Production depends on completing a series of tasks

Failure or quality reduction of any one task reduces the value of the entire product

You can’t substitute quantity for quality (Adrian’s example: two mediocre chefs can’t replace a great chef in making an amazing meal)

In Adrian’s example, quality of each step/person is measured by a coefficient (q) between 0 and 1, and the process has 10 steps. Improving the quality in each step from 0.5 to 0.75, a 50% improvement, yields a 600% improvement in output.

I’d argue that the entire process of software development and delivery meets the three conditions for the O-ring theory to apply. You can probably generalize this more broadly to the entire organization/company, but satisfying the 2nd condition may be more challenging.

Adrian’s implications, applied to talent will look something like the following:

A single “weak link” overall output dramatically. It’s not enough to hire top talent for some roles. You need to be good across the board.

Small differences in quality quickly compound to make very large differences between the performance of the best-in-class and the rest

The better you already are, the more value you get from improving your weaknesses. Conversely, if you’re fairly poor across the board, you won’t get as high a return on investment on an improvement in one specific area as a company with a higher overall level would. These forces tend to lead to ‘skill-matching’ – fairly uniform levels of performance across the talent pool of a given organisation

A different way to articulate #3 is that the more great workers a company already has, the more incremental value another great worker adds. This, to some degree, rationalizes some of the behaviors we’re seeing in the market where top performing companies are willing to pay more for top talent – it’s not just because they can, it’s because they should…

But it also calls into question another practice that’s becoming more common in these top performing companies. Some of them, like Google, use the growing proof that talent is not distributed normally (which I covered here) to justify paying their employees “unfairly” and legitimizing substantial (3x-5x and sometime even more) pay differences for employees at the same level. But if the 10x difference in output can be explained, not by the existence of a single 10x engineer, but by the existence of 10 engineers that are only 10% better than average, does that still make sense?

I don’t reference a lot of HBR articles in this blog, but I came across this one, by Donald Sull (et. el) recently and it really struck a cord with me, since it talks about strategy execution first and foremost from an organizational perspective:

Sull and his co-authors make their case by debunking 5 strategy execution myths:

Myth 1: Execution equals alignment – alignment down the chain-of-command is a solved problem and most corporate processes to manage it (MBOs, tying bonuses to goals, etc.) are working well. The true, unsolved problem is around cross-departmental coordination:

“Only 9% of managers say they can rely on colleagues in other functions and units all the time, and just half say they can rely on them most of the time… When managers cannot rely on colleagues in other functions and units, they compensate with a host of dysfunctional behaviors that undermine execution”

Myth 2: Execution means sticking to the plan – strategy execution fails when companies “stick to the plan” too much, rather than seize fleeting opportunities that support the strategy. Perhaps the most extreme case of this behavior, is disinvestment from opportunities that did not pan out as expected:

“Companies also struggle to disinvest… Top executives devote a disproportionate amount of time and attention to businesses with limited upside and send in talented managers who often burn themselves out, trying to save businesses that should have been shut down or sold years earlier”

Myth 3: Communication equals understanding – there’s a growing appreciation for the criticality of organizational clarity in driving strategy execution and the important role that internal communication plays in creating that clarity. However, internal communication initiatives often center around optimizing the wrong metric:

“Not only are strategic objectives poorly-understood, but they seem unrelated to one another and disconnected from the overall strategy… Part of the problem is that executives measure communication in terms of inputs, rather than by the only metric that actually counts – how well key leaders understand what’s communicated”

Myth 4: Performance culture drives execution – this issue is tied directly to the first myth. If the culture emphasized individual performance over collaboration and coordination, it gets in the way of removing the true roadblocks for execution:

“The most pressing problem with many corporate cultures, however, is that they fail to foster the coordination that, as we’ve discussed, is essential to execution. Companies consistently get this wrong. When it comes to hires, promotions and non-financial recognition, past performance is two or three times more likely than a track record of collaboration to be rewarded“

Myth 5: Execution should be driven from the top – in complex organizations, effective execution requires dealing with a constant stream of tough trade-offs: should we invest the time in coordinating with another department at the cost of losing a fleeting opportunity? should we say “no” to a client request that’s misaligned with the strategy at the cost of losing revenue? The leaders closest to the situation are the ones who can respond the quickest and are best positioned to make the tough call:

“Frequent and direct intervention from on high encourages middle managers to escalate conflicts rather than resolve them, and over time they lose their ability to work things out with colleagues in other departments. Moreover, if top executives insist on making the important calls themselves, the diminish middle-managers’ decision making skills, initiative, and ownership of results”

At the end of the day, Sull and team paint a rather grim picture of a commonly used myth-driven strategy execution approach. But if we choose to look at the glass half full, they also outline the path for a more effective strategy execution approach:

Joel builds on Ben Horowitz’s description of the CEO as the owner of the information architecture in the company.

He captures the crux of the CEO’s challenges as a leader in this quote:

I naturally end up with a unique picture of the whole company, since I’m learning insights from all the different teams and areas. I see patterns across multiple areas, and this leads me to ideas for making changes that could make the whole company more effective.

That’s where the danger comes. I’m both in one of the best positions to notice and implement changes to how we work, and also I’m far removed enough that I might be missing some context about how my ideas for changes could have negative implications.

He then outlines his approach to dealing with this challenge:

I try to have the communication architecture to put me in the best position to understand a lot of the context and to draw patterns between challenges in different areas.

I aim to notice the challenges arising in areas, and spend time to reflect on them in a way that others might not have the viewpoint or time to do so.

Once I start to find myself moving towards a solution for challenges, I stop myself.

I then speak with people who will be affected by any potential changes to solve the challenge I’ve found.

When I speak with people, I try to share all the context, without a solution.

Sometimes I may have a hint of a solution in my mind, however I try to be fully open to a different solution being the optimal one, which I can only learn based on speaking with people.

The goal and result of this method is that often I’m not even the one who comes up with solutions, and the changes we make are more fully embraced.

Steps 1 and 2 are the hallmarks of a good leader, but it’s in step 3 where great leaders get separated from the good. It takes tremendous discipline to stop yourself when you think you know the answer. And rather than issue an edict to execute your solution, loop in the affected people, describe the problem that you’re seeing and the big-picture context that they may be missing, and let them come up with the solution themselves.